[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/introducing-gitlab-credits":3,"navigation-en-us":38,"banner-en-us":448,"footer-en-us":458,"blog-post-authors-en-us-Manav Khurana":700,"blog-related-posts-en-us-introducing-gitlab-credits":715,"assessment-promotions-en-us":745,"next-steps-en-us":784},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":26,"isFeatured":11,"meta":27,"navigation":28,"path":29,"publishedDate":20,"seo":30,"stem":34,"tagSlugs":35,"__hash__":37},"blogPosts/en-us/blog/introducing-gitlab-credits.yml","Introducing Gitlab Credits",[7],"manav-khurana",null,"product",{"featured":11,"template":12,"slug":13},false,"BlogPost","introducing-gitlab-credits",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"updatedDate":21,"body":22,"category":9,"tags":23},"Introducing GitLab Credits, usage-based pricing for GitLab Duo Agent Platform","Learn how GitLab Credits helps reduce costs and provides flexibility for agentic AI in the enterprise software development lifecycle.\n",[18],"Manav Khurana","https://res.cloudinary.com/about-gitlab-com/image/upload/v1768314648/gvy4pfqjaeahkoagsjmr.png","2026-01-15","2026-02-10","We built GitLab Credits because seat-based pricing for agentic AI was not making sense.\n\nSeat-based pricing creates AI “haves\" and \"have-nots” for engineering teams, a fundamental misalignment with the way that modern agentic AI should be used across the software development lifecycle. Today, you have to buy a seat for every individual before they can start using AI. While this works for the few heavy users, it can be too expensive and unfair for the majority of the team with light or spiky usage. That's why in many organizations, only a portion of the team gets to have an “AI seat.\"\n\nAdd to that, [GitLab Duo Agent Platform](https://about.gitlab.com/blog/gitlab-duo-agent-platform-is-generally-available/) is different from Duo Pro, Duo Enterprise, and other AI developer tools in the market. Agents and agentic workflows can be invoked by your team when they need AI assistance and triggered by SDLC events running in the background. With Duo Agent Platform, agentic AI is no longer only tied to user seats.\n\nGitLab Credits addresses these issues as our new virtual currency for usage-based pricing, starting with GitLab Duo Agent Platform. That means, every member in your organization with a GitLab account (Premium or Ultimate) can now use agentic AI capabilities without you paying for an AI seat, whether invoked by them or set up as background agents.\n\n## How GitLab Credits work\n\nGitLab Credits are pooled across your entire organization. Your GitLab Duo Agent Platform usage is drawn down from GitLab Credits. That includes both synchronous and asynchronous use of agents and agentic flows. This includes:\n\n* [Foundational agents](https://docs.gitlab.com/user/duo_agent_platform/agents/foundational_agents/) such as Security Analyst, Planner, and Data Analyst\n\n* [Foundational flows](https://docs.gitlab.com/user/duo_agent_platform/flows/foundational_flows/) such as Code Review, Developer, and Fix CI/CD Pipeline\n\n* [External agents](https://docs.gitlab.com/user/duo_agent_platform/agents/external/) such as Anthropic Claude Code and OpenAI Codex\n\n* Custom agents and flows you build and publish in your [GitLab AI Catalog](https://docs.gitlab.com/user/duo_agent_platform/ai_catalog/)\n\n* [Agentic Chat](https://docs.gitlab.com/user/gitlab_duo_chat/agentic_chat/) in the GitLab UI and in the IDE used by your developers\n\n**Note:** External agents are available to try at no cost in 18.8 and do not consume GitLab Credits. We will be introducing pricing next month with our 18.9 release. Custom flows are currently in beta and do not consume GitLab Credits.\n\nThe amount of credits drawn down is based on the number of agentic requests by large language models ([more details here](https://docs.gitlab.com/subscriptions/gitlab_credits/#models)). As more LLMs become available, we will certify them for use with GitLab Duo Agent Platform and add to this list, providing customers with a transparent view of how they are consumed.\n\nThe total count of GitLab Credits is calculated at the end of the month based on actual usage. This model also automatically offsets usage from power users against that of lighter users, effectively lowering your total cost of AI for every individual (as compared to paying per seat for every individual).\n\nFor simplicity, each GitLab Credit has an **on-demand** list price of $1. You can use GitLab Duo Agent Platform without any commitments and usage is billed monthly (at the end of each month). For enterprise customers that sign up for **annual commitments**, we offer volume discounts for monthly credits.\n\nAs a limited-time promotion[*](#notes), all GitLab customers that have active Premium and Ultimate subscriptions will automatically receive $12 and $24 in **included credits per user**, respectively. These credits will refresh every month until the end of the promotion period and give your team access to all GitLab Duo Agent Platform features at no extra cost. When you accept our billing terms, any usage above these included credits will be billed through committed monthly credits or on-demand credits.\n\n## Cost governance with GitLab Credits\n\n**Sizing GitLab Credits:** Your account team has a sizing calculator as part of the GA of GitLab Duo Agent Platform to estimate the number of GitLab Credits you’ll need every month. This calculator was built with usage patterns we’ve observed during the beta period. In addition, as an existing or a new customer, you can request a free trial to confirm your estimated actual usage.\n\n**Usage visibility:** With the 18.8 release, you have detailed usage information through two complementary dashboards — one in the GitLab Customers Portal for billing managers focused on financial oversight, and one in-product for administrators focused on operational monitoring. Both provide attribution of usage, cost breakdowns, and historical trends so you always know exactly how your credits are being consumed. If you follow a cross-charging practice internally, you’ll be able to use project- and group-level rollups for cost allocations.\n\n**Usage controls:** You can enable or disable GitLab Duo Agent Platform access for specific teams or projects, ensuring only approved usage can tally up to your credits. We also plan to add user-level controls shortly after GA to help you manage who can use GitLab Duo Agent Platform capabilities and draw-down credits.\n\n**Automated usage notifications:** We’ll proactively keep you informed about your GitLab Credit usage via email alerts when you reach 50%, 80%, and 100% of your committed monthly credits, giving you time to adjust usage, purchase additional commitments, or plan for on-demand billing.\n\n## Upgrading from seat-based GitLab Duo Pro/Enterprise to GitLab Credits for Duo Agent Platform\n\nIf you’ve purchased and are using GitLab Duo Pro and Duo Enterprise, you can keep using those capabilities as supported options. You can upgrade to GitLab Duo Agent Platform at any time and do what you can with “classic” Duo and access new capabilities such as agentic chat, additional foundational agents, custom agents and flows, external agents, and more.\n\nAt the time of upgrade, we will roll forward your investment in seats for GitLab Duo Pro and Duo Enterprise to GitLab Credits for Duo Agent Platform. The remaining dollar amount of seat commitments will be exchanged for monthly GitLab Credits with volume-based discounts. The monthly GitLab Credits can then be shared across every team member in your organization you allow, not just the users who had assigned Duo seats before.\n\n## Competitive comparison: GitLab Credits vs. seat-based pricing\n\n| Benefit | GitLab Credits | Seat-based pricing |\n| ----- | ----- | ----- |\n| **AI for everyone** | Every approved team member gets AI access from day one | Creates AI \"haves\" and \"have-nots\" — forces seat rationing |\n| **No upfront Investment**  | Start small with included credits, increase commitment as ROI becomes clear | Must purchase seats upfront before proving value |\n| **Pay for what you use** | Only the AI work actually performed above included tier is billed | Pay per seat regardless of actual usage |\n| **Optimized spend** | Shared credit pool allows you to offset power users with light users | Must pay for light users, overages for premium requests from power users |\n| **Detailed visibility** | Usage dashboards with detailed attribution and historical trends | Limited insight into which users drive value |\n| **Granular cost controls** | Choose who can access, proactive alerts, and upcoming budget controls to limit | Limit who gets a seat to control costs |\n| **Sizing flexibility**  | Calculator to estimate monthly credits, with more unit discounts with volume | Count who gets a seat multiplied by price per seat |\n| **Simplified contracts and billing** | Single SKU and bill covers all agentic capabilities across the DevSecOps lifecycle | Multiple AI licenses required across different third-party tools |\n\n## Getting started\nNew customers to GitLab can try Duo Agent Platform right away for free with a [GitLab Ultimate trial](https://about.gitlab.com/free-trial/devsecops/).\n\nOrganizations with active GitLab subscriptions can start using Duo Agent Platform right away with their included credits. [Reach out to sales](https://about.gitlab.com/sales/) to explore additional options to try Duo Agent Platform capabilities.\n\n1. **For existing Premium/Ultimate customers**: GitLab Duo Agent Platform is already available for customers with active Premium and Ultimate licenses[**](#notes) via included credits. GitLab Self-Managed customers will gain access when they upgrade to the GitLab 18.8 release. GitLab Dedicated customers will be upgraded to GitLab 18.8 during their scheduled maintenance window in February and will be able to use Duo Agent Platform from that point.\n2. **Enable GitLab Duo**: Ensure GitLab Duo Agent Platform is enabled in your namespace settings.\n\n3. **Start exploring**: Use your included monthly GitLab Credits to try GitLab Duo Agent Platform capabilities.\n\n4. **Go beyond included credits:** You may opt in to GitLab Credits for expanded usage beyond included credits at the on-demand list price. For volume discounts with commitment, please [contact us](https://about.gitlab.com/sales/) to get a quote for your specific usage level.\n\nVisit our [GitLab Duo Agent Platform documentation](https://docs.gitlab.com/user/duo_agent_platform/) to learn more about getting started.\n\n## Notes\n\n\\* These included promotional credits are available for a limited time at GA, and subject to change at GitLab’s discretion.\n\n** Excludes GitLab Duo with Amazon Q and GitLab Dedicated for Government customers.\n\n> To learn more about GitLab Duo Agent Platform and all the ways agentic AI can transform how your team works, [visit our GitLab Duo Agent Platform page](https://about.gitlab.com/gitlab-duo-agent-platform/). If you are an existing GitLab customer, reach out to your GitLab account manager or partner to schedule a live demonstration of our platform capabilities.\n\n## GitLab Credits FAQ\n\n**1\\. What are GitLab Credits and why did GitLab introduce them?**\n\nGitLab Credits is a new virtual currency for usage-based GitLab capabilities, starting with GitLab Duo Agent Platform. GitLab introduced this model because seat-based pricing was forcing organizations to ration AI access within engineering teams, and Duo Agent Platform usage is not just tied to seats. Credits are pooled across your entire organization, allowing you to give every team member access to AI capabilities, or set up background agentic workflows, without requiring individual seat purchases upfront.\n\n**2\\. How does credit consumption work?**\n\nCredits are drawn down based on the number of agentic requests made, with different rates depending on which LLM is used. For example, you get two model requests per credit for Claude-sonnet-4.5 (the default for most features), and 20 requests per credit for models like gpt-5-mini or claude-3-haiku.\n\n**3\\. What's included for existing Premium and Ultimate customers?**\n\nAs a limited-time promotion, customers with active Premium and Ultimate subscriptions automatically receive included credits free of charge alongside the GA release of Duo Agent Platform in GitLab 18.8:\n\n* $12 in credits per user per month for Premium\n* $24 in credits per user per month for Ultimate\n\nIncluded credits are at a per-user level, refresh monthly, and enable access to all GitLab Duo Agent Platform features at no extra cost. Usage above these included credits will be billed separately. These included promotional credits are available for a limited time after GA, and subject to change at GitLab’s discretion.\n\n**4\\. How can I control and monitor credit usage?**\n\nGitLab provides multiple governance tools: detailed usage dashboards in both the Customers Portal and in-product, the ability to enable/disable access for specific teams or projects, upcoming user-level controls, and automated email alerts at 50%, 80%, and 100% of committed monthly credits. We also expect to offer a sizing calculator to estimate your monthly credit needs.\n\n**5\\. How do I get started with GitLab Duo Agent Platform?**\n\nFor existing Premium/Ultimate customers, access is automatic on GitLab.com SaaS. Self-Managed customers gain access when upgrading to GitLab 18.8. Simply enable GitLab Duo Agent Platform in your namespace settings and start exploring using your included monthly credits. For usage beyond included credits, you can opt-in to on-demand billing or contact GitLab for volume discounts with annual commitments.\n\n**6\\. How can I try GitLab Duo Agent Platform if I don't already have a Premium or Ultimate subscription?**\n\nNew customers to GitLab can try GitLab Duo Agent Platform by starting a [GitLab Ultimate trial](https://about.gitlab.com/free-trial/devsecops/).\nOrganizations with active GitLab subscriptions can start using Duo Agent Platform right away with their included credits. [Reach out to sales](https://about.gitlab.com/sales/) to explore additional options to try Duo Agent Platform capabilities.\n\n*This blog post contains \"forward-looking statements\" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934\\. Although we believe that the expectations reflected in these statements are reasonable, they are subject to known and unknown risks, uncertainties, assumptions and other factors that may cause actual results or outcomes to differ materially. Further information on these risks and other factors is included under the caption \"Risk Factors\" in our filings with the SEC. 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Officer",{},"/en-us/blog/authors/manav-khurana",{},"en-us/blog/authors/manav-khurana","WPf_e-a2ANF9NZNGy_Bgnh0lD4PNHo-M2Mvj_vKvTUg",[716,728,734],{"content":717,"config":726},{"title":718,"description":719,"authors":720,"heroImage":722,"date":723,"body":724,"category":9,"tags":725},"GitLab 18.11: Budget guardrails for GitLab Credits","Learn how new spending caps and per-user credit limits give organizations the budget guardrails to scale GitLab Duo Agent Platform.",[721],"Bryan Rothwell","https://res.cloudinary.com/about-gitlab-com/image/upload/v1776259080/cakqnwo5ecp255lo8lzo.png","2026-04-16","Teams using GitLab Duo Agent Platform with on-demand GitLab Credits are shipping faster, catching bugs earlier, and automating tasks that used to take entire sprints. But as adoption grows, so does oversight from finance, procurement, and platform teams to prove that AI spending is bounded, predictable, and controllable.\n\nOne of the greatest barriers to broader AI adoption isn't skepticism about the technology. It's uncertainty about managing spend. Without budget caps, a busy month could produce unexpected expenses. Without per-user limits, a handful of power users could burn through the team's credits before the month is over. And without either, engineering leaders who want to expand their use of agentic AI for software development have to jump through more hoops for budget approval.\n\nSince its [general availability](https://about.gitlab.com/blog/gitlab-duo-agent-platform-is-generally-available/), GitLab Duo Agent Platform has provided usage governance and visibility. With GitLab 18.11, we're introducing usage controls for [GitLab Credits](https://about.gitlab.com/blog/introducing-gitlab-credits/): spending caps and budget guardrails that give your organization even more control and transparency over how credits are consumed.\n\n## Managing GitLab Credits\n\nGitLab 18.11 adds three layers of control over GitLab Credits consumption: a subscription-level spending cap, per-user credit limits, and visibility into cap status and enforcement.\n\n### Subscription-level spending cap\n\nBilling account managers can now set a hard monthly ceiling for on-demand GitLab Credits consumption for their entire subscription.\n\nHere's how it works:\n\n* **Set a cap** in the `Customers Portal` under your subscription's GitLab Credits settings.  \n* **Enforce spend limits automatically.**  When on-demand usage reaches the cap, DAP access is paused for all users on that subscription until the next monthly period begins.  \n* **Make adjustments as you go.** Raise or disable the cap mid-month to restore access.\n\nThe cap resets each monthly period and your configured limit carries forward unless you change it. Because usage data is synchronized periodically rather than in real time, a small amount of additional usage may occur after the cap is reached before enforcement takes effect. See the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for details.\n\n### User-level spending caps\n\nNot every user consumes credits at the same rate, and that's expected. But when one or two power users account for a disproportionate share of the pool, the rest of the team can lose access before the month is over.\n\nPer-user credit caps prevent any single user from consuming more than their fair share:\n\n* **Flat per-user cap.** Set a uniform credit limit that applies equally to every user on the subscription through the GitLab GraphQL API. Unlike the subscription-level cap, the per-user cap applies to a user's total consumption across all credit sources.  \n* **Custom per-user overrides.** For organizations that need differentiated limits, you can set individual credit caps for specific users through the GraphQL API. For example, you could give your staff engineers a higher allocation while applying a standard limit to the broader team.  \n* **Individual enforcement.** When a user reaches their cap, they retain full access to GitLab. Only their Duo Agent Platform credit usage is paused until the next billing cycle. Everyone else keeps working uninterrupted until they hit their own limit or the subscription-level cap is reached, whichever comes first.\n\n### Visibility and notifications\n\nWhen a subscription-level cap is reached, GitLab sends an email notification to billing account managers so they can take action: raise the cap, wait for the next period, or redistribute credits.\n\nWithin GitLab, group owners (GitLab.com) and instance administrators (Self-Managed) can view which users have been blocked due to reaching their per-user cap and restore access by adjusting the cap through the GraphQL API. \n\n## How budget guardrails help organizations scale AI usage\n\nGuardrails are essential as organizations ramp up their AI adoption. Here's why:\n\n### Predictable AI budgets\n\nUsage controls for GitLab Duo Agent Platform turn AI into a bounded, predictable budget item using on-demand GitLab Credits. That makes it easier to deploy agents across the software development lifecycle and get sign-off from finance, justify renewals, and plan quarterly spend.\n\n### Governance and chargeback\n\nLarge organizations often need to align AI consumption with internal budgets, cost centers, or departmental policies. Per-user caps give platform teams a straightforward mechanism to allocate credits fairly and track consumption at the individual level. The API import options make it practical to manage caps at enterprise scale. Combined with per-user usage data from the GitLab Credits dashboard, organizations can track consumption patterns to inform their own internal chargeback or budget allocation processes.\n\n### Confidence to scale\n\nMany customers start GitLab Duo Agent Platform with a small pilot group. Usage controls remove risks associated with expanding that pilot across the organization. You can roll out Duo Agent Platform to hundreds or thousands of developers knowing there's a hard ceiling protecting your budget. If usage grows faster than expected, you'll hit the cap, not an unexpected invoice.\n\n## Addressing the seat-based and visibility conundrum\n\nMany AI coding tools take a seat-based approach to cost management. You buy a fixed number of seats at a flat per-user price, and that's your budget. It's simple, but rigid. You pay the same whether a developer uses the tool ten times a day or never touches it. And as vendors introduce premium models and usage-based overages on top of seat pricing, the cost predictability that seat-based licensing promised starts to erode.\n\n\nGitLab takes a different approach. Usage-based pricing with hard caps and a single governance dashboard. You get the flexibility of paying for what your teams actually use, with the budget predictability of enforced spending limits.\n\n## Real-world usage controls\n\n**One example is a mid-size SaaS customer that wants to protect their monthly budget.** A 200-person engineering organization sets a subscription-level cap equal to their expected on-demand usage. Their VP of Engineering can confidently tell finance that GitLab Duo Agent Platform spend will never exceed the approved amount, even as they onboard new teams. If they approach the cap mid-month, the billing account manager gets a notification and can decide whether to raise the limit or wait for the next period.\n\n**At GitLab, we also work with large enterprises that want to keep usage fair across teams.** A global financial services company with 2,000 developers uses per-user caps to ensure equitable access. Staff engineers working on complex refactoring projects get a higher individual allocation via API, while most developers receive a standard flat cap. No single user can exhaust the pool, and the platform team uses the per-user usage data in the GitLab Credits dashboard to track consumption patterns and inform quarterly budget planning.\n\n## Getting started\n\nUsage controls are available for both GitLab.com and Self-Managed customers running GitLab 18.11. Different controls are configured in different places depending on the scope and your role.\n\n**Subscription-level cap**\n\nBilling account managers set the subscription-level on-demand cap in the Customers Portal:\n\n1. Sign in to the `Customers Portal`.  \n2. On your subscription card, navigate to **GitLab Credits** settings.  \n3. Enable the monthly on-demand credits cap and enter your desired limit.\n\n**Flat per-user cap**\n\nThe flat per-user cap can be set through the GitLab GraphQL API by namespace owners (GitLab.com) or instance administrators (Self-Managed). Check the [GitLab Credits documentation](https://docs.gitlab.com/subscriptions/gitlab_credits/) for the latest on available configuration surfaces.\n\n**Custom per-user overrides**\n\nFor differentiated limits, namespace owners (GitLab.com) and instance administrators (Self-Managed) can set individual caps programmatically. This is useful for automation and infrastructure-as-code workflows.\n\n**Monitor usage and cap status**\n\n* **Customers Portal:** View detailed usage and cap status.  \n* **GitLab.com:** Group owners can view blocked users under **Settings > GitLab Credits**.  \n* **Self-Managed:** Instance administrators can view cap status and blocked users under **Admin > GitLab Credits**.\n\n## GitLab Duo Agent Platform is ready to scale\n\nUsage controls are available now in GitLab 18.11. If you've been waiting for the right guardrails before expanding GitLab Duo Agent Platform across your organization, this is your moment. Set your caps, roll out Duo Agent Platform to more teams, and start shipping faster!\n\n> [Learn more about GitLab Credits and usage controls](https://docs.gitlab.com/subscriptions/gitlab_credits/).",[9,24,25],{"featured":11,"template":12,"slug":727},"gitlab-18-11-budget-guardrails-for-gitlab-credits",{"content":729,"config":732},{"title":730,"heroImage":722,"description":731,"date":723,"category":9},"GitLab 18.11 release","This release includes Agentic SAST Vulnerability Resolution, Data Analyst Foundational Agent, CI Expert Agent, and more.",{"featured":11,"template":12,"externalUrl":733},"https://docs.gitlab.com/releases/18/gitlab-18-11-released/",{"content":735,"config":743},{"title":736,"description":737,"authors":738,"heroImage":722,"date":723,"body":740,"category":9,"tags":741},"GitLab 18.11: CI Expert and Data Analyst AI agents target development gaps","Set up CI and query your software development lifecycle data with two new GitLab Duo Agent Platform foundational agents available in GitLab 18.11.",[739],"Corinne Dent","AI-generated code moves faster than the systems around it can keep up with. More code means more merge requests queued, more pipelines to configure, more questions about delivery that nobody has time to answer — and most of the tooling teams rely on wasn't built for this pace.\n\nIn GitLab 18.11, two new foundational agents for Duo Agent Platform address specific gaps in the development lifecycle that AI has largely left untouched:\n* CI Expert Agent (now in beta) focuses on the gap between writing code and getting it into a running pipeline\n* Data Analyst Agent (now generally available) focuses on the gap between shipping code and being able to answer basic questions about how that delivery is actually going.\n\n\nThese are problem areas that couldn't be solved by a general-purpose assistant. A tool running outside GitLab can generate a YAML file or answer a question, but it has no awareness of how your pipelines have historically performed, where failures cluster, or what your actual MR cycle times look like. That context lives in GitLab. These agents do too.\n## Fast CI setup with CI Expert Agent\n\nAI has made it easier than ever to write code. Getting that code into a running pipeline is still something most teams do days, or weeks, later — if at all. The blank-page problem isn't in the editor anymore. The blank page is now in `.gitlab-ci.yml`.\n\nDevelopers who have never configured CI don't know what language detection looks like in YAML, what their test commands should be, or how to validate the result before pushing. Teams either copy a config from a previous project that may not fit, stitch together examples from documentation, or wait for the one person who's done it before. If that person isn't available, CI becomes the thing you'll \"get to later.\" Later becomes never.\n\nWhen CI never happens, the impact shows up everywhere else. Changes ship without a reliable safety net, regressions surface in production instead of in pipelines, and work piles up in bigger, riskier batches because no one wants to be the person who “breaks the build.” Over time, teams normalize working in the dark, often relying on undocumented institutional knowledge and ad-hoc testing, instead of having a fast, predictable feedback loop baked into every change.\n\nCI Expert Agent, now available in beta, removes that friction. It inspects your repository, identifies your language and framework, and proposes a working build and test pipeline tailored to what's actually there — then explains every decision in plain language. The target: a running pipeline in minutes, with no YAML written by hand.\n\nWhat CI Expert Agent does:\n\n* Repo-aware pipeline generation detects language, framework, and test setup \n* Generates valid, runnable build and test configurations   \n* Guided first-pipeline flow with plain-language explanation of each step in Agentic Chat  \n* Native GitLab CI semantics with no config translation required\n\nBecause it runs inside GitLab and sees real pipeline behavior over time, each improvement can build on how teams actually work, not just on static examples.\n\u003Ciframe src=\"https://player.vimeo.com/video/1183458036?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"CI/CD Expert Agent\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nCI Expert Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium, Ultimate Editions with Duo Agent Platform enabled.\n\n## Query GitLab data in plain language with Data Analyst Agent\n\nAI has sped up how teams ship. Answering basic questions about how that work is going has gotten harder, not easier.\n\nHow long are MRs sitting in review? Which pipelines are slowing teams down? Are deployment targets actually being hit? These questions used to be answerable by glancing at a dashboard. Now, with more code, more teams, and more complexity, the data exists — it's in GitLab — but accessing it still means waiting on an analytics team, filing a dashboard request, or learning GLQL.\n\nData Analyst Agent targets that gap. Ask a natural-language question and get an instant visualization in Agentic Chat. No query language, no dashboard request, no waiting for the answers to be assembled by someone else.\n\nFor example, the agent can answer questions about the following topics for these roles:\n\n* Engineering managers: MR cycle time, throughput by project, where reviews get stuck  \n* Developers: Contribution patterns, flaky tests blocking their MRs, pipeline speed trends  \n* DevOps and platform engineers: Pipeline success/failure rates, runner utilization, deployment frequency  \n* Engineering leadership: Cross-portfolio deployment frequency, project health metrics, lead time comparisons\n\nNow generally available in 18.11, the agent covers MRs, issues, projects, pipelines, and jobs — full software development lifecycle coverage, expanded from the beta scope. Because Data Analyst Agent queries what's already in GitLab, the context is always current, and there's no pipeline to maintain or third-party tool to keep synchronized. Generated GitLab Query Language queries can be copied and used anywhere GitLab Flavored Markdown is supported, with direct export to work items and dashboards on the roadmap.\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1183094817?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"Data Analyst agent demo\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\u003Cbr>\u003C/br>\n\nData Analyst Agent is available on GitLab.com, Self-Managed, Dedicated; Free, Premium and Ultimate Edition with Duo Agent Platform enabled.\n\n## One platform, connected context\n\nBoth agents run inside GitLab, with access to the code, pipelines, issues, and merge requests already there. That's what separates platform-native AI from a disconnected assistant: the context is always current, and it only gets more useful over time. CI Expert Agent and Data Analyst Agent represent two concrete steps toward a platform where AI doesn't just help you write code faster; it helps you understand, ship, and maintain what gets built.\n\n> [Start a free trial of GitLab Duo Agent Platform](https://about.gitlab.com/gitlab-duo/) to experience these foundational AI agents.",[24,742,9],"features",{"featured":28,"template":12,"slug":744},"ci-expert-and-data-analyst-ai-agents-target-development-gaps",{"promotions":746},[747,761,772],{"id":748,"categories":749,"header":751,"text":752,"button":753,"image":758},"ai-modernization",[750],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":754,"config":755},"Get your AI maturity score",{"href":756,"dataGaName":757,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":759},{"src":760},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":762,"categories":763,"header":764,"text":752,"button":765,"image":769},"devops-modernization",[9,568],"Are you just managing tools or shipping innovation?",{"text":766,"config":767},"Get your DevOps maturity score",{"href":768,"dataGaName":757,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":773,"categories":774,"header":776,"text":752,"button":777,"image":781},"security-modernization",[775],"security","Are you trading speed for security?",{"text":778,"config":779},"Get your security maturity score",{"href":780,"dataGaName":757,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":782},{"src":783},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":785,"blurb":786,"button":787,"secondaryButton":792},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":788,"config":789},"Get your free trial",{"href":790,"dataGaName":49,"dataGaLocation":791},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":504,"config":793},{"href":53,"dataGaName":54,"dataGaLocation":791},1776430032471]